Deep learning-based image captioning

A Common problem linking computer vision and natural language processing is the ability to generate an accurate caption for a given image. In this paper, various approaches of image captioning models towards achieving state of the art results are studied. After the various approaches are studied, th...

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Main Author: Chong, Kaydon
Other Authors: Zhang Hanwang
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2019
Subjects:
Online Access:https://hdl.handle.net/10356/136507
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1365072019-12-20T07:22:47Z Deep learning-based image captioning Chong, Kaydon Zhang Hanwang School of Computer Science and Engineering hanwangzhang@ntu.edu.sg Engineering Engineering::Computer science and engineering A Common problem linking computer vision and natural language processing is the ability to generate an accurate caption for a given image. In this paper, various approaches of image captioning models towards achieving state of the art results are studied. After the various approaches are studied, the best approaches are then extracted and then recombined into a new single model in hopes to achieve a new state of the art model. A comparison of each model’s result will be used to determine the best performing model to be implemented. In this paper, we study the model of 2 different groups that created their image captioning model. They are namely the Google Brain team and the team that won the 2017 Visual Question Answering (VQA) Challenge in 2017. Bachelor of Engineering (Computer Science) 2019-12-20T07:22:47Z 2019-12-20T07:22:47Z 2019 Final Year Project (FYP) https://hdl.handle.net/10356/136507 en application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Engineering
Engineering::Computer science and engineering
spellingShingle Engineering
Engineering::Computer science and engineering
Chong, Kaydon
Deep learning-based image captioning
description A Common problem linking computer vision and natural language processing is the ability to generate an accurate caption for a given image. In this paper, various approaches of image captioning models towards achieving state of the art results are studied. After the various approaches are studied, the best approaches are then extracted and then recombined into a new single model in hopes to achieve a new state of the art model. A comparison of each model’s result will be used to determine the best performing model to be implemented. In this paper, we study the model of 2 different groups that created their image captioning model. They are namely the Google Brain team and the team that won the 2017 Visual Question Answering (VQA) Challenge in 2017.
author2 Zhang Hanwang
author_facet Zhang Hanwang
Chong, Kaydon
format Final Year Project
author Chong, Kaydon
author_sort Chong, Kaydon
title Deep learning-based image captioning
title_short Deep learning-based image captioning
title_full Deep learning-based image captioning
title_fullStr Deep learning-based image captioning
title_full_unstemmed Deep learning-based image captioning
title_sort deep learning-based image captioning
publisher Nanyang Technological University
publishDate 2019
url https://hdl.handle.net/10356/136507
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